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charltonmediagroup

LinkedIn Ads MCP Server

search_targeting_entities

Search LinkedIn Ads targeting entities such as job titles, skills, industries, and companies to refine audience segments.

Instructions

Search for targeting entities like job titles, skills, industries, companies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
facetYesTargeting facet to search
queryYesSearch query
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, and the description does not disclose behavioral traits such as whether search is case-sensitive, supports partial matching, returns paginated results, or has rate limits. The agent lacks critical information for correct invocation and interpretation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no waste. However, it could be more informative without losing conciseness, e.g., by mentioning result format or search behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and low behavioral transparency, the description is incomplete. Agents need to know if results are paginated, what fields are returned, or if there are limits. The current description only defines the tool's broad purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with both parameters described adequately in the schema. The description adds examples of entity types but does not clarify format or behavior beyond the schema. Baseline 3 is appropriate given high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches for targeting entities, listing examples like job titles, skills, industries, companies. The verb 'search' combined with resource 'targeting entities' distinguishes it from sibling tools that create, update, or list campaigns and audiences.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for finding targeting entities but provides no explicit guidance on when or when not to use it, nor does it mention alternatives. Given the sibling tools are mostly CRUD operations for campaigns and audiences, the usage context is implicit but not detailed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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